1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.00 1.00
## LDevsum 1.00 1.00
## dh0 1.01 1.04
## dh1 1.01 1.04
## dl0 1.03 1.12
## dl1 1.00 1.01
## dl2 1.01 1.03
## dl3 1.03 1.11
##
## Multivariate psrf
##
## 1.02
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1209.74847 | 24073.260 |
| DIC3 | 1150.00435 | 20874.776 |
| PWAIC | 41.32281 | 1130.462 |
| WAIC | 1176.03329 | 21356.916 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1 1.01
## dh0 1 1.01
## dh1 1 1.01
##
## Multivariate psrf
##
## 1
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H0a | |
|---|---|
| DIC | 1212.56780 |
| DIC3 | 1149.04492 |
| PWAIC | 41.00079 |
| WAIC | 1174.90840 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1.009 1.045
## dl0 1.046 1.186
## dl1 1.077 1.305
## dl2 0.999 0.999
## dl3 1.075 1.295
##
## Multivariate psrf
##
## 1.07
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L7 | |
|---|---|
| DIC | 24078.92 |
| DIC3 | 20872.70 |
| PWAIC | 1130.17 |
| WAIC | 21355.41 |